U.S. telecommunication infrastructure is estimated to consume 60 billion kilowatt hours of power per year. Such an enormous consumption partially results from the fact that most networks are engineered to handle peak traffic. Network devices such as routers and switches tend to operate at full speed and consume maximum power, while typical traffic levels are only a small fraction of the maximum throughput.
One known approach to reducing energy consumption in a network involves powering down particular network devices from time to time. For example, these network devices may be placed into a sleep mode, an off state or other type of inactive state in which power consumption of the network device is considerably reduced relative to its maximum power consumption. However, during such downtime any packets arriving at the network device for processing have to be buffered, and this can cause significant delay in the transport of the packets through the network. Thus, minimizing the period of time that the network devices are in their respective active states and minimizing delays in packet transmission through the network become two conflicting goals. This problem is compounded by the fact that there is often a considerable transition time involved in switching a given network device between its active and inactive states.
In order to address the costs associated with transition of network devices between their active and inactive states, it has been proposed that edge routers of a network group packets having the same source and destination and transmit them in bursts, in order to reduce the number of transitions and increase the inactive time of the network devices. See S. Nedevschi et al., “Reducing Network Energy Consumption via Sleeping and Rate-Adaptation,” in J. Crowcroft and M. Dahlin, eds., NSDI, pp. 323-336, USENIX Association, 2008. However, such an approach can still lead to considerable delay for packet transmission through the network, and fails to provide a global optimization that simultaneously addresses both energy consumption and delay minimization.
Improved techniques that simultaneously address both energy consumption and delay minimization are disclosed in U.S. patent application Ser. No. 12/723,116, filed Mar. 12, 2010 and entitled “Network Scheduling for Energy Efficiency,” which is incorporated by reference herein. In one of the disclosed techniques, a communication network comprising a plurality of network devices is configured to implement scheduling for energy efficiency. More particularly, a set of network devices interconnected in a line within a network is identified, and a common frame size is established. For each of the network devices of the line, active and inactive periods for that network device are scheduled in a corresponding frame having the common frame size, with the frames in the respective network devices of the line being time shifted relative to one another by designated offsets. For each of one or more of the active periods of each of the network devices of the line, received packets are scheduled for processing in that network device. Such an arrangement improves the energy efficiency of a communication network by scheduling active and inactive periods for particular nodes of the network in a coordinated manner that minimizes the impact of transitions between active and inactive periods on packet delay.
Another issue that arises in a communication network relates to scheduling data packets for processing in a manner that ensures that queue length within a given network device remains bounded over time. Numerous scheduling algorithms have been developed that ensure bounded queue length. However, such scheduling algorithms generally assume that the network device processor always operates at its full rate whenever that network device is in an active state. Although this may be optimal for clearing queue backlogs as fast as possible, it is often suboptimal in terms of energy consumption, and therefore undermines the energy efficiency of the overall network.